Quick Demo

Sachin Yadav, IIT Gandhinagar, sachin.yadav@iitgn.ac.in

IRIS Flower data set

The data set contains information about three species of IRIS flowers namely:

• Iris setosa
• Iris versicolor
• Iris virginica

Four features are collected from each sample, sepal-length, sepal-width, petal-length and petal-width in centi-meters.

# Common imports
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

import plotly.express as px

iris_df = pd.read_csv("./data/IRIS.csv.gz", compression="gzip")
iris_df.sample(5)

	Unnamed: 0	sepal_length	sepal_width	petal_length	petal_width	species
144	144	6.7	3.3	5.7	2.5	Iris-virginica
48	48	5.3	3.7	1.5	0.2	Iris-setosa
52	52	6.9	3.1	4.9	1.5	Iris-versicolor
23	23	5.1	3.3	1.7	0.5	Iris-setosa
78	78	6.0	2.9	4.5	1.5	Iris-versicolor

fig = px.scatter_3d(iris_df, x='sepal_length', y='sepal_width', z='petal_width',
              color='species', template="plotly_dark")
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

COVID-19 Dataset

covid_df = pd.read_csv("./data/owid-covid-data.csv.gz", compression="gzip")
covid_df.sample(5)

	Unnamed: 0	iso_code	continent	location	date	total_cases	new_cases	new_cases_smoothed	total_deaths	new_deaths	...	female_smokers	male_smokers	handwashing_facilities	hospital_beds_per_thousand	life_expectancy	human_development_index	excess_mortality_cumulative_absolute	excess_mortality_cumulative	excess_mortality	excess_mortality_cumulative_per_million
81551	81551	KWT	Asia	Kuwait	2020-10-08	109441.0	698.0	537.857	642.0	3.0	...	2.7	37.0	NaN	2.0	75.49	0.806	NaN	NaN	NaN	NaN
22911	22911	BRN	Asia	Brunei	2020-09-11	145.0	0.0	0.000	3.0	0.0	...	2.0	30.9	NaN	2.7	75.86	0.838	NaN	NaN	NaN	NaN
23353	23353	BRN	Asia	Brunei	2021-11-27	14992.0	74.0	78.286	97.0	0.0	...	2.0	30.9	NaN	2.7	75.86	0.838	NaN	NaN	NaN	NaN
109821	109821	NER	Africa	Niger	2020-12-16	2361.0	0.0	40.429	82.0	0.0	...	0.1	15.4	8.978	0.3	62.42	0.394	NaN	NaN	NaN	NaN
145776	145776	SYR	Asia	Syria	2021-09-15	29974.0	169.0	146.000	2097.0	7.0	...	NaN	NaN	70.598	1.5	72.70	0.567	NaN	NaN	NaN	NaN

5 rows × 68 columns

required_columns = ["iso_code", "location", "continent", "date", "new_cases_smoothed", "total_cases"]
covid_df = covid_df.dropna(subset = required_columns)

covid_df = covid_df.sort_values("date")

covid_df[['iso_code', 'location']].sample(8)

	iso_code	location
37754	CUW	Curacao
19499	BES	Bonaire Sint Eustatius and Saba
113350	NOR	Norway
63674	GIN	Guinea
14759	BLR	Belarus
732	AFG	Afghanistan
15405	BEL	Belgium
48293	SWZ	Eswatini

Covid-19 New Cases Worldwide on 23 December 2021

covid_day_df = covid_df[covid_df.date == "2021-12-23"]
covid_day_df.sample(5)

	Unnamed: 0	iso_code	continent	location	date	total_cases	new_cases	new_cases_smoothed	total_deaths	new_deaths	...	female_smokers	male_smokers	handwashing_facilities	hospital_beds_per_thousand	life_expectancy	human_development_index	excess_mortality_cumulative_absolute	excess_mortality_cumulative	excess_mortality	excess_mortality_cumulative_per_million
98588	98588	MEX	North America	Mexico	2021-12-23	3940401.0	3319.0	1876.571	298359.0	198.0	...	6.9	21.4	87.847	1.38	75.05	0.779	NaN	NaN	NaN	NaN
97077	97077	MRT	Africa	Mauritania	2021-12-23	40308.0	69.0	49.143	860.0	1.0	...	NaN	NaN	15.950	NaN	64.92	0.546	NaN	NaN	NaN	NaN
149550	149550	TLS	Asia	Timor	2021-12-23	19833.0	0.0	0.429	122.0	0.0	...	6.3	78.1	28.178	5.90	69.50	0.606	NaN	NaN	NaN	NaN
94423	94423	MDV	Asia	Maldives	2021-12-23	94444.0	145.0	116.429	261.0	1.0	...	2.1	55.0	95.803	NaN	78.92	0.740	NaN	NaN	NaN	NaN
88477	88477	LTU	Europe	Lithuania	2021-12-23	507916.0	1772.0	1467.571	7223.0	23.0	...	21.3	38.0	NaN	6.56	75.93	0.882	NaN	NaN	NaN	NaN

5 rows × 68 columns

fig = px.scatter_geo(covid_day_df, locations="iso_code", color="continent",
                     hover_name="location", size="new_cases_smoothed",
                     projection="natural earth", template="plotly_dark")

fig.show()

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
c:\Users\cheta\IDSassignment\writing-assignment-chetan_shubh\_notebooks\demo.ipynb Cell 14' in <module>
      <a href='vscode-notebook-cell:/c%3A/Users/cheta/IDSassignment/writing-assignment-chetan_shubh/_notebooks/demo.ipynb#ch0000013?line=0'>1</a> fig = px.scatter_geo(covid_day_df, locations="iso_code", color="continent",
      <a href='vscode-notebook-cell:/c%3A/Users/cheta/IDSassignment/writing-assignment-chetan_shubh/_notebooks/demo.ipynb#ch0000013?line=1'>2</a>                      hover_name="location", size="new_cases_smoothed",
      <a href='vscode-notebook-cell:/c%3A/Users/cheta/IDSassignment/writing-assignment-chetan_shubh/_notebooks/demo.ipynb#ch0000013?line=2'>3</a>                      projection="natural earth", template="plotly_dark")
----> <a href='vscode-notebook-cell:/c%3A/Users/cheta/IDSassignment/writing-assignment-chetan_shubh/_notebooks/demo.ipynb#ch0000013?line=4'>5</a> fig.show()

File ~\AppData\Local\Programs\Python\Python310\lib\site-packages\plotly\basedatatypes.py:3400, in BaseFigure.show(self, *args, **kwargs)
   <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/basedatatypes.py?line=3366'>3367</a> """
   <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/basedatatypes.py?line=3367'>3368</a> Show a figure using either the default renderer(s) or the renderer(s)
   <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/basedatatypes.py?line=3368'>3369</a> specified by the renderer argument
   (...)
   <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/basedatatypes.py?line=3395'>3396</a> None
   <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/basedatatypes.py?line=3396'>3397</a> """
   <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/basedatatypes.py?line=3397'>3398</a> import plotly.io as pio
-> <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/basedatatypes.py?line=3399'>3400</a> return pio.show(self, *args, **kwargs)

File ~\AppData\Local\Programs\Python\Python310\lib\site-packages\plotly\io\_renderers.py:397, in show(fig, renderer, validate, **kwargs)
    <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/io/_renderers.py?line=391'>392</a>         raise ValueError(
    <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/io/_renderers.py?line=392'>393</a>             "Mime type rendering requires ipython but it is not installed"
    <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/io/_renderers.py?line=393'>394</a>         )
    <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/io/_renderers.py?line=395'>396</a>     if not nbformat or LooseVersion(nbformat.__version__) < LooseVersion("4.2.0"):
--> <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/io/_renderers.py?line=396'>397</a>         raise ValueError(
    <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/io/_renderers.py?line=397'>398</a>             "Mime type rendering requires nbformat>=4.2.0 but it is not installed"
    <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/io/_renderers.py?line=398'>399</a>         )
    <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/io/_renderers.py?line=400'>401</a>     ipython_display.display(bundle, raw=True)
    <a href='file:///~/AppData/Local/Programs/Python/Python310/lib/site-packages/plotly/io/_renderers.py?line=402'>403</a> # external renderers

ValueError: Mime type rendering requires nbformat>=4.2.0 but it is not installed

Covid-19 Total Cases over the days

fig = px.scatter_geo(covid_df, locations="iso_code", color="continent",
                     hover_name="location", size="total_cases",
                     projection="natural earth", animation_frame="date", template="plotly_dark")

fig.show()

MNIST Dataset

import torchvision
import os

import matplotlib.pyplot as plt
from matplotlib import rc
from matplotlib.animation import FuncAnimation
from matplotlib import animation

rc('animation', html='jshtml')

frn = 10 # Number of frames to process in the animation
fps = 0.5 # Frames per second
mywriter = animation.PillowWriter(fps=fps) 

mnist_dataset = torchvision.datasets.MNIST(root = "data/mnist", train = True, download = True, transform=torchvision.transforms.ToTensor())

fig, ax = plt.subplots(figsize = (10, 10))

def change_plot(frame_idx):
    ax.cla()
    image_tensor = mnist_dataset[frame_idx][0]
    image_tensor_gray = image_tensor[0]
    image_tensor_gray = image_tensor_gray * 255
    ax.matshow(image_tensor_gray, cmap = "gray")
    for i in range(image_tensor_gray.shape[0]):
        for j in range(image_tensor_gray.shape[1]):
            ax.text(i, j, str(int(image_tensor_gray[j][i].item())), va = "center", ha = "center", color = "blue", fontsize = "small")
    ax.axis("off")
    plt.tight_layout()

anim = FuncAnimation(fig, change_plot, frn, interval=1000 / fps)
plt.close()
anim

Once Loop Reflect

<Figure size 432x288 with 0 Axes>

mywriter = animation.PillowWriter(fps=fps)

if not os.path.exists("./assets/gif"):
    os.makedir("./assets/gif")
    
anim.save('./assets/gif/mnist.gif',writer=mywriter)

<Figure size 432x288 with 0 Axes>